01
Prepare cases with less effort.
Bring evidence from approved sources together for the people making decisions.
Phrony / AI agents for
Financial services.
More time for decisions. Less time gathering evidence.
Put agents to work on onboarding, investigations and reporting. Help teams prepare cases with less manual work, clear approvals and a record of what happened.
Self-host Phrony on your infrastructure.
Onboarding. Investigations. Reporting.
Estimate your ROIMove the case forward. Keep the controls.
A shared runtime for the work that matters. Start with one agent and measure what changes.
02
Help customers move forward.
Identify missing information and prepare clearer answers during onboarding and service.
03
Build on one foundation.
Use a shared runtime for new agent responsibilities across your products and operations.
Watch an example
Agents for the work behind every decision.
Choose an agent. Follow the request, each step, then the result. Some examples finish a useful draft. Others pause for a person to review.
Choose an example
The request
Review the KYC file for Northstar Trading and tell me what still needs attention.
- Retrieve the customer file
- Compare screening evidence
- Prepare the review pack
Run the example to see the agent work through this request.
Illustrative run with sample data. No live systems are connected.
Make the business case
Less manual work. What is it worth?
Use your own workload and costs to explore an agent’s potential value. Start with one responsibility you know well.
Potential capacity freed / month
125 hours
Today300 h
With an agent175 h
- Net value, year one
- €36,000
- ROI, year one
- 114%
- Simple payback
- 2.1 months
Modelled staff capacity value, not guaranteed cash savings. Validate handling time and quality with your own agent.
How the estimate works
Hours freed per month = cases × (current human minutes − future human minutes) ÷ 60. Annual capacity value = hours freed × hourly cost × 12. Year-one net value subtracts 12 months of running costs and one-time implementation. ROI divides net value by those total costs. Simple payback divides implementation cost by monthly capacity value after running costs. The model assumes a full year at the selected volume after launch and excludes ramp-up, taxes and financing. Negative time savings remain negative; payback is not reached when monthly net value is zero or below.
Governance for production agents
EU AI Act readiness
As agents take more consequential actions, control and evidence become part of the product.
- 01Reviewable definitions
Make an agent’s purpose, tools and boundaries explicit.
- 02Human checkpoints
Require approval for designated tool actions.
- 03Execution records
Keep a record of runs for investigation and review.
These controls support compliance work. EU AI Act compliance depends on the complete system, use case and your role; a runtime alone does not establish it.
And in the US?
Requirements vary by state and sector. Texas’s TRAIGA is one applicable AI law. The NIST AI Risk Management Framework is voluntary guidance, not a law or certification. Map obligations to your own deployment.
These examples are just the start
Your ideas. The sky’s the limit.
Customer-facing or behind the scenes: build an agent around the job your business needs done. Connect your tools, define its boundaries and self-host the runtime.